Wen | Xiao Liu
Editor|Xiao Liu
preface
Sustainable management of tropical forests in Central Africa has been identified as an important way to improve unsustainable logging practices in tropical forests.
It is bound by international commitments and forest policies, which are spelled out at the level of legal instruments, requiring concessionaire management measures to be derived from literature and scientific experiments, much of which focuses on the rehabilitation of developed areas.
Using a formula defined by De Madron, the reconstruction of exploited forests in the Congo Basin countries was determined.
The formula takes into account some structural parameters of the developed species (minimum diameter developed, average annual growth). In addition, several other parameters, such as deforestation damage and mortality, were taken into account, but the researchers did not agree on this.
The central metric of the formula is rotation, which represents a hypothetical period in which at least 50% of the forest's exploited potential is restored. It varies between Central African countries from 20 to 30 years and applies to one species or group of species.
Cameroon chose a 30-year rotation period, with local managers selecting at least 20 species among the main species.
The need for long-term replenishment of resources is a major issue for forest management. Timber production has been significantly reduced and forest concessions run the risk of being abandoned by the ownership company due to insufficient profits. The plot can then be converted into an agricultural area, eliminating most of the functions it fulfills.
In addition to this species reconstruction, the conservation and sustainable management of forests requires a better understanding of their heterogeneity, the environmental drivers of their composition, and their vulnerability to climate change.
Cameroonian rainforest
From the perspective of implementing sustainable forest management, the effectiveness of the reconstructed formula, the maintenance of the diversity index and other parameters such as density, cross-sectional area and diameter structure remain problematic.
Variability in forest structure and diversity between different sites of the same forest has been poorly studied and documented according to local conditions. However, these parameters are essential for the identification of indicators of forest ecosystem dynamics and are an important basis for forest ecosystem development.
To this must be added the spatial structure of species, which is one of the key parameters for understanding ecological processes and forest ecosystem functioning.
The material selected first
The site selected is a commercial production forest that was inventoried twice in eastern Cameroon in 2003 and 2020, with a tropical climate with two dry seasons (early June to late July and mid-November to mid-March) and two rainy seasons (mid-March to early June and August to mid-November).
The average annual precipitation is 1367±208 mm, the average monthly temperature is 23.9°C ± 0.7°C, and the average relative humidity is 76.4% ± 2.2%.
The undulations of the massif are relatively uneven, with extreme heights varying between 506 and 801 meters, with some swamps, sometimes very expansive. The soil mainly encountered on the surface is ferritic type, which is derived from metamorphic source rock alteration.
The flora is located in the Guinea-Congo region and consists of semi-deciduous dense moist forests with Sycamore and Ulmus.
In this rainforest area, three sites were named:
● AME: This is the annual harvesting area grouped by site developed after the first management inventory (2003) and at least 10 years before the second (2020);
NonAme: Utilized before the first management inventory;
NonExpl: No mining has taken place since the concession was granted to the production forest.
Introduction to the location of the study area and the equipment that manages the inventory
Through complex data screening and selection
Each plot consists of 250 meters long and 20 meters wide (i.e. 0.5 hectares) on an equidistant line where all trees with a chest height diameter (DHP) of more than 20 cm have been counted.
For each tree, the tree species was determined and the breast diameter was measured using a tape measure. Then on a table that provides information to identify the strain, the generic name of the identified species, the corresponding code, the breast diameter grade and, in some cases, the code indicating the quality of the tree are added to each row.
Once this information is calculated from the row number, a link is established with a database of all known species to add the scientific name, genus, family, group, and minimum managed harvest diameter (DMA). Based on the row number, different sites have been added along with their total area and survey area.
The two databases thus constituted are precisely grouped together in the first column of the inventory year (2003 or 2023), and the comparison between DBH category and DMA makes it possible to add status for each species (available for species with at least DMA or no).
The composition of the flora expressed in terms of the number of each taxon in the population, independent of the number of individuals represented in the taxon, is determined individually for each management inventory stage, all sites and each site, including all species or only major species.
and take all individuals (TI) or only available individuals, i.e. individuals whose DBH is greater than or equal to DBH equals DMA (IE). It's also a matter of highlighting taxon elements that are in one stage of the manifest but not another.
It is calculated based on three sites (Ame, NonAme, and NonExpl). It is calculated according to the following formula:
The cross-sectional area (m2/ha) is the cumulative sum of the ratio of the area occupied by the base of the trunk to the area of the site. It is calculated according to the following formula:
where: G: cross-sectional area; π: 3.14;i : Thoracic diameter grade (grade 1 includes stems of 20 to 30 cm...) Level 13 includes stems from 140 to 150 cm ... ）； N i: number of individuals in category i; dm i: median diameter of the category (dm 1 = 25 ... dm 13 = 145 ... ）。
Floral composition
The floristic composition of all list species and major species of both lists was observed at each site, grouping the individuals inventoried according to species, genera and family.
The data show that in 2003, the first census area was 277 hectares, with a total of 36,615 people in 61 families, 311 species, 210 genera, and 61,647 people in 501 hectares, 314 species and 223 genera in 58 families. During the second inventory in 2020, the number of major species was 43 species in 34 genera in 15 families at the time of the first inventory and 35 genera in 16 families at the time of the second inventory.
This specific composition is not exactly the same when viewed at the level of the three sites, either for all species or for the main species.
The area surveyed during the first inventory (2003) was 94.5 hectares for Ame sites, 27.5 hectares for NonAme sites and 155 hectares for NonExpl sites.
The second inventory (2020) was 166 ha, 48.5 ha and 286.5 ha respectively.
None of the three sites contains all the species found in each inventory, and the number of species between the first and second inventories is higher in the "NonExpl" site for all individuals and available individuals.
The number of species in the "NonAme" site is small.
The most representative genus in all three locations is cherimoya. Ulmus and Combretaceae are also the five most represented genera of all sites, but with different frequencies.
Floral composition of species inventoried at different sites.
The number of individuals, families, genera and species listed by all species and major species.
TI = All Individuals
The percentage is the proportion of the dominant species to all species.
The number of individuals, families, genera and species of species inventoried at three sites.
For all individuals, at site A, the family Erythropalaceae was found in the first list, but not in the second.
On the botanical website, Asteraceae, honeysuckle and willow families were found in the second list, but not in the first.
On the N site, Pentagonidae and Primulaceae are found in the first list, but not in the second.
Since forest management issues are sustainable use, special attention must be paid to the main tree species available for use.
The floristic composition of the main species at different locations on the farm
The graph shows that during the first and second inventories, the number of major species recorded was higher at N sites (41 and 40, respectively), followed by Ame sites (39 and 36) and finally No sites (28 and 34).
The most important species recorded in both lists appeared at all study sites.
The floristic composition of the main species at different locations on the farm.
Structural parameters
When calculating the density of all individuals, all individuals with DBH greater than or equal to 20 cm, and so-called available individuals, are taken into account. That is, those individuals whose DBH is greater than or equal to DMA, as shown in the figure.
The results of the first inventory showed an average density of 132 stems/ha for all individuals and 21 stems/ha (≥DMA) for available individuals.
Within the framework of the second inventory, developable individuals reduced by 3 plants/ha, significantly (P < 0.05) 9 plants/ha.
A significant decrease in density between the first and second inventories was observed at the Amé and NonAme sites (P < 0.05), with the most significant differences recorded at the Ame site, with 24 stems/ha, of which 7 stems/ha were represented by available individuals.
This reduction represents 20 stems/ha in the NonAme site, of which 1 stem/ha is used for exploitability.
The total density of the main tree species during the first inventory was 23 plants/ha, which was a very significant difference from the second inventory (20 plants/ha) (P < 0.05).
This apparent difference (P < 0.05) was observed at the Ame and No site levels, but not at the NonExpl site level, and by looking at the available individuals in the same group, there was only a significant difference between the results of the two inventories at the Ame site level (P < 0.05).
Based on an analysis of development data from Cameroon from 2007 to 2018, 17 species were identified as the most exploited species in forest concessions, and of these, three species were not found at our study site.
There is Ben's Ben clover. They are not found in the concession and Lophira. (Azobé) found in the concession, but not at the study site, the remaining 14 species, and the other two main species mainly represented in the list, belong to the most exploited species and the largest number.
Base area
The base area is directly related to the volume of standing wood, so its increment is a measure of wood production.
It is theoretically a unitless number (the ratio of two surfaces), but in practice the result is expressed in m2/ha.
The figure shows the change in base area between the two inventories.
During the first inventory in 2003, the base area of all species found was 269 m2/ha, which decreased to 225 m2/ha during the second inventory in 2020, which decreased between the first and second inventories and varied according to the study area.
Notably, the cross-sectional area of the AME sites for all inventoried species and major species was reduced by 30% and 35%, respectively. This difference also exists on the NonAme site (12% and 13%, respectively), with the most developed species best illustrating the impact of the base area. The figure shows the evolution of the base area at different sites between the two management inventories according to the most exploited species.
Between 2003 and 2020, the most utilized species accounted for 68% and 69% of the main species, respectively, and 26% of all inventories. In the massifs studied, the main exploited species are mostly abundant.
The change in base area between the two lists.
The cross-sectional area decreased from 2003 to 2020, however, the production of soybean pterostilbene and African pterostilbene increased.
The relationship between data and geographic location
The inventory data for this plot is consistent with the phytogeographic description, and in fact, the forest formations encountered are identified as dense semi-deciduous moist forests.
In terms of the number of species on the list, the five most representative families (55%) are the family Soursop (13 genera), the legume family (48 genera), Euphorbiaceae (19 genera), Sycamore (11 genera) and Oleander (6 genera).
Among the major species, Pterostilbene and African Pterostilbene were the most important, accounting for 30% of the individuals recorded in the first inventory and 31% in the second inventory.
One of the fundamental characteristics of dense tropical forests is the large number of representative species, and the result of this diversity is that individuals of a given species usually appear only at very low densities. In addition, according to Cameroonian regulations, only 17% of the stock stems are proposed for development as the main tree species, of which only 25% are exploitable. This result shows that the value of existing species in our forest ecosystems is very low.
The first and second inventories were conducted at the same site, but the location of the survey plots was different, indicating that the layout of the survey plan was likely to capture or lose species.
In fact, of the 311 species identified in the 2003 inventory data, 82 were not found in the 2020 inventory data.
The same is true for 31 genera and 3 families (Acidwood, Sycamores, Goldenrodae), conversely, of the 314 species identified in the 2020 inventory data, 85 were not found in the 2003 inventory data, as were 44 genera and 2 families (Redwood, Primulaceae).
Basic characteristics and types of dense tropical forests
Specific diversity analyses of the three sites showed that species diversity varied from site to site.
In fact, after the first management inventory, the number of species on the Ame site (258) was lower than the number of species on the No site (273).
The latter has remained undeveloped since the study plot allocation, and this difference can also be demonstrated by the previous exploitation of the forest between 1969 and 1995 during the permitted felling.
The decrease and/or increase in species between two inventories at the same study site may be due to differences in inventory layout positioning, which can also be demonstrated by a development process that reduces the available potential of the development area.
The 1% survey results do not provide a complete flora composition of a site, and depending on the equipment used for sampling schemes, some taxa may appear or disappear, with densities varying depending on the area of development or non-development.
Species densities ranged from 140 to 127 plants/ha in the first inventory and from 129 to 111 plants/ha in the second inventory, depending on the study area.
This density is lower than the density found in the DynAfFor Network project, which only covers the majority of 323 to 674 plants/ha in the Congo Basin forest.
This is equivalent to 100 species per hectare found in tropical forests in Central Africa, which is lower than the nearly 300 species per hectare found in the Amazon forest.
Species within the same concession and in the same type of forest have a very disproportionate distribution of richness.
In fact, the density was higher in the "Amé" area (140 plants/ha), followed by the NonAme area (132 plants/ha) and the "NonExpl" area (127 plants/ha) with lower density.
This change in distribution can reveal the fact that the operating company prefers the most fertile areas for mining during the plots and interim agreements.
end
The flora composition between the two stages shows a change in the site studied, which cannot be attributed to a modification of the route positioning carrying the plot.
Sites that have not experienced any deforestation, more than 80 species found in one phase are not encountered in another, therefore, as a basis for a management plan, this inventory is carried out at a reduced rate (0.5% to 1%) and does not provide any guarantee for the identification of all resources, it is desirable to make annual management decisions to improve the sustainable management of forests.